Active Microbial Communities Inhabit Sulphate-Methane Interphase in Deep Bedrock Fracture Fluids in Olkiluoto, Finland

Hindawi Publishing Corporation BioMed Research International Volume 2015, Article ID 979530, 17 pages http://dx.doi.org/10.1155/2015/979530

Research Article Active Microbial Communities Inhabit Sulphate-Methane Interphase in Deep Bedrock Fracture Fluids in Olkiluoto, Finland

Malin Bomberg,1 Mari Nyyssönen,1 Petteri Pitkänen,2 Anne Lehtinen,2 and Merja Itävaara1

1 VTT Technical Research Centre of Finland, P.O. Box 1000, 02044 Espoo, Finland 2Posiva Oy, Olkiluoto, 27160 Eurajoki, Finland

Correspondence should be addressed to Malin Bomberg; [email protected]

Received 6 January 2015; Accepted 4 March 2015

Academic Editor: Weixing Feng

Copyright © 2015 Malin Bomberg et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Active microbial communities of deep crystalline bedrock fracture water were investigated from seven different boreholes in Olkiluoto (Western Finland) using bacterial and archaeal 16S rRNA, dsrB, and mcrA gene transcript targeted 454 pyrosequencing. Over a depth range of 296–798 m below ground surface the microbial communities changed according to depth, salinity gradient, and sulphate and methane concentrations. The highest bacterial diversity was observed in the sulphate-methane mixing zone (SMMZ) at 250–350 m depth, whereas archaeal diversity was highest in the lowest boundaries of the SMMZ. Sulphide-oxidizing 𝜀-proteobacteria (Sulfurimonas sp.) dominated in the SMMZ and 𝛾-proteobacteria (Pseudomonas spp.) below the SMMZ. The active archaeal communities consisted mostly of ANME-2D and Thermoplasmatales groups, although Methermicoccaceae, Methanobacteriaceae, and Thermoplasmatales (SAGMEG, TMG) were more common at 415–559 m depth. Typical indicator microorganisms for sulphate-methane transition zones in marine sediments, such as ANME-1 archaea, 𝛼-, 𝛽-and𝛿-proteobacteria, JS1, Actinomycetes, Planctomycetes, Chloroflexi, and MBGB Crenarchaeota were detected at specific depths. DsrB genes were most numerous and most actively transcribed in the SMMZ while the mcrA gene concentration was highest in the deep methane rich groundwater. Our results demonstrate that active and highly diverse but sparse and stratified microbial communities inhabit the Fennoscandian deep bedrock ecosystems.

1. Introduction Deep subsurface microbial communities of the Fenno- scandian Shield, including Olkiluoto, are functionally diverse Stable deep terrestrial subsurface locations are presently and play a role in a variety of redox reactions, such as nitrate, being considered for long-term geological disposal of spent iron, and sulphate reduction, as well as methanogenesis nuclear fuel. Microbe-mediated processes may play a key (e.g., [3–6]). While the presence of these processes has been role in the long-term stability and risk assessments of such confirmed by cultivation based techniques4 [ , 5, 7]andDNA- storage. Dissolved sulphide produced by sulphate reducing based PCR techniques [3, 6, 8], activity of these processes in bacteria (SRB), for example, may exert influence on spent situ remains uncertain. nuclearfuelcanistercorrosionleadingtomobilityofradionu- In general, deep subsurface microbial communities clides [1]. In Olkiluoto, Finland, spent nuclear fuel will be appear to have extraordinarily low metabolic activity [6]. disposed approximately 450 m deep in the bedrock. There- However, under certain environmental conditions, such as fore,understandingtheroleandfunctionalityofmicrobial sulphate-methane transition zones (SMTZ), microbial activ- communities in this environment is of critical importance for ity appears to increase dramatically [9, 10]. At SMTZs in ma- the safety of the spent nuclear fuel repository [2]. rine sediments, concentrations of H2Sincrease(e.g.,[11, 12]) 2 BioMed Research International possibly due to anaerobic oxidation of methane (AOM) and almost 60 boreholes drilled for research and monitoring 2− simultaneous reduction of SO4 . In addition, both microbial purposes and studies on the chemistry and microbiology cell concentration and microbial diversity have been seen to of the groundwater have been on-going since the 1980s be elevated in sedimentary SMTZ environments [10]. Little is [2]. The groundwater in Olkiluoto is stratified relative to known of the activity, function, and composition of microbial physicochemical parameters [18]. From the surface to a depth communities in methane-rich deep terrestrial groundwater of30mbgslthewaterisofmeteoricorigin(i.e.precipitation) or terrestrial groundwater SMMZs. and the water type is fresh to brackish. The uppermost Methane and sulphates are major constituents of Olk- 100 mbgsl has a high concentration of dissolved inorganic iluoto groundwater, residing in different groundwater layers carbon (as bicarbonates), and salinity (as total dissolved [2]. Sulphate-rich water prevails at depths above 300 m solids [TDS] and chlorine) increases with depth. Between below ground surface level (mbgsl) and methane-rich water 100 and 300 mbgsl, salinity is roughly similar to the present dominates below 300 mbgsl. A sulphate-methane mixing day Baltic Sea, but, below 300 mbgsl, the salinity increases −1 zone (SMMZ) can be identified between 250 and 350 mbgsl up to 84 g TDS L at 1000 mbgsl. Based on drill core [2]. In contrast to the clearly identifiable sharp SMTZs logging, the bedrock of Olkiluoto consists mainly of gneiss formed in anaerobic aquatic sediments [13, 14] the SMMZs (9% of the bedrock volume), migmatitic gneiss (64% of the in deep terrestrial groundwater are broad. In deep terrestrial bedrock volume), TGG (tonalite-granodiorite-granite) gneiss subsurface, groundwater resides in bedrock fractures, which (8%), and pegmatitic granite (19%) [19]. In addition, of the may be almost isolated and thereby exhibit stagnant ground- migmatitic gneiss 67% is veined and 33% diatexitic gneiss. 2− water or well connected with each other, which enables Between 100 and 300 mbgsl, the SO4 concentration is different degrees of groundwater flow. In addition, strong elevated in ancient (i.e., pre-Baltic) seawater derived ground- environmental changes, such as infiltration of surface water, water. Below this layer, the methane concentration in the − 2− crustal rebound, glaciation or deglaciation can affect the water increases and Cl dominates whereas SO4 is almost stability and position of the SMMZ [15]. absent. A mixing zone where methane-rich groundwater Recently Pedersen et al. [16] simulated SMMZ mixing diffuses into sulphate-rich groundwater (a sulphate-methane effect in Olkiluoto groundwater. By gradually increasing the mixing zone, SMMZ) can be identified at 250 to 350 mbgsl concentration of sulphate in methane-rich and sulphate-poor depth. This zone is characterized by increased concentration groundwater over an experimental period of 103 days, the of sulphide and a decrease in sulphate and methane. ∘ authors showed that the composition of the microbial com- The temperature rises linearly with depth, from ca. 5-6 C ∘ munity was strongly influenced by sulphate and methane. at 50 mbgsl to ca. 20 C at 1000 mbgsl [20]. The pH of the Several studies in Olkiluoto also show that the microbial water is slightly alkaline throughout the depth profile. Several communities in Olkiluoto groundwater are stratified and aquifer zones, such as zones HZ20 or HZ21, span several potentially affected by the groundwater SMMZ [3, 6, 17]. different boreholes (Table 1). 𝛿-and𝛾-proteobacteria are generally found in water layers 𝛽 aboveandintheSMMZwhile -proteobacteria become more 2.2. Sampling. Deep groundwater samples (Table 1)from abundant in the deeper methane-rich water [3, 6]. A clear specific fracture zones were collected from seven different increase in the number of methanogens was also detected boreholes in Olkiluoto (Figure 1) between December 2009 simultaneously with a decrease in the number of sulphate and May 2010. Fracture zones were isolated by permanent reducing bacteria (SRB) in Olkiluoto deep groundwater [3, or temporary inflatable packers as described previously [3]. 17]. In addition, analysis of methyl coenzyme M reductase Packer-sealed fracture zones were purged by pumping for (mcrA) gene clone libraries demonstrates the presence of at least four weeks prior to sampling in order to allow putative anaerobic methane oxidizing group 1 (ANME-1) indigenous fracture water to fill the isolated borehole section. archaea at 300–400 m depth [3]. Here, we extend this research and use RNA-targeted Anaerobic groundwater was pumped from the borehole high-throughput (HTP) sequencing to investigate the active directly in to an anaerobic chamber (MBRAUN, Germany) SRB and methanogen communities of the methane-rich deep through a sterile, gas-tight polyacetate tube (8 mm outer groundwater around the depth of the nuclear waste reposi- diameter), where samples were collected in acid-washed, tory rising up in to the SMMZ at the Olkiluoto site. In order sterile2LSchottglassbottles(DuranGroupGmBH,Ger- to study the active microbial community in fracture water many). Microbial biomass for nucleic acid analyses was samples, the bacterial and archaeal 16S rRNA pools were also concentrated from 500 mL and 1000 mL samples by vacuum characterized and used as proxy for active (living) microbial filtration through cellulose acetate membranes (0.2 𝜇mpore cells. In addition, the abundance of SRB and methanogen size, Corning, MA, USA) inside the glove box. Filters were communities was studied by qPCR targeting dissimilatory then cut out from the filter funnels and frozen on dry ice in sulfite reductase (dsrB) and mcrA transcripts and genes. sterile 50 mL cone tubes (Corning MA, USA). Frozen samples weretransportedondryicetothelaboratorywheretheywere ∘ 2. Materials and Methods stored at −80 Cpriortoanalysis. Samples for microbial cell counts were collected in 2.1. Description of the Site. The island of Olkiluoto is the acid-washed sterile, anaerobic 100 mL glass infusion flasks selected site for deep (approximately 450 mbgsl) geological equipped with butyl rubber septa and aluminium crimp caps ∘ disposal of spent nuclear fuel in Finland. The island has andtransportedtothelaboratoryat4C in a light-proof BioMed Research International 3

Table 1: The geochemical and biological measurements from the samples collected from fracture fluids from seven different boreholes in Olkiluoto, Finland. The different boreholes are presented as sampling depths.

296m 328m 347m 415m 559m 572m 798m Borehole OL-KR13 OL-KR6 OL-KR23 OL-KR49 OL-KR2 OL-KR1 OL-KR29 Depth below ground −296.11 −328.37 −346.52 −415.45 −559.15 −572.24 −797.81 surface (m)

Water type Brackish SO 4 Brackish SO4 Saline Saline Saline Saline Saline −1 −8 −7 −7 −7 −7 −7 −9 Transmissivity (m2 s )5.86× 10 1.31 × 10 6.48 × 10 4.37 × 10 4.33 × 10 5.50 × 10 (<10 ) Hydrogeological zone HZ001 HZ20A HZ21 HZ21 −1 Pump rate (mL min ) 22 104 20 172 23.9 62.1 6.1 Cumulative volume fracture fluid removed 1129 5486 971 7509 1251 4492 496 (L) Sampling date 9.3.2010 18.5.2010 15.12.2009 14.12.2010 27.1.2010 26.1.2010 18.5.2010 Microbiology Sampling date 1.3.2010 10.5.2010 7.12.2009 1.12.2009 18.1.2010 18.1.2010 3.5.2010 Chemistry

Sampling date CH4 6.3.2006 3.8.2005 18.3.2003 13.5.2003 4.4.2005 ∘ Temperature ( C) 19.6 11.6 17.6 11 14.8 12 17.7 pH 7.9 7.9 7.5 8.1 8.6 7.8 7.3 −1 Ec (mS m ) 897 1832 2190 2670 4110 3770 7820 −1 DIC (mgC L ) 27 4.1 3.9 <3 <3.75 <3.75 <21 −1 NPOC (mgC L )10<2.4 5.1 <3115<12 −1 TDS (mg L ) 4994 10655 12733 15899 25459 23261 53205 −1 Alk (m) meq L 2.19 0.37 0.28 0.16 0.29 0.23 0.13 2− −1 SO4 (mg L ) 79.5 379 2.9 1.4 0.5 0.5 <2 − −1 S2 (mg L ) 5.10 NA 0.62 0.02 <0.02 0.13 <0.02 −1 < < < < < < < NO3 (mg L ) 0.01 0.01 0.01 0.01 0.01 0.01 0.01 −1 < < < NH4 (mg L ) 0.07 0.03 0.02 0.02 0.02 0.04 0.08 −1 Fe2+ (mg L ) <0.02 NA 0.08 0.53 <0.02 0.40 0.46 −1 Na2+ (mg L ) 1320280025303110498047209150 −1 K+ (mg L ) 8.2 9.3 8.3 9.6 19 20 27 −1 Ca2+ (mg L ) 460 1100 2100 2700 4600 3700 10000 −1 Mg2+ (mg L )357755191852136 − −1 Cl (mg L ) 2920 6230 7930 9940 15700 14600 33500 −1 CH4 (mL L )2222NANA386272920 −1 TNC (mL ) 4.2 × 105 1.0 × 105 2.5 × 105 1.5 × 104 5.9 × 104 8.7 × 104 2.3 × 104 4 3 4 4 1 3 −1∗ 3.1 × 10 5.4 × 10 1.4 × 10 1.6 × 10 6.5 × 10 2.2 × 10 dsrB gene copies mL 0 (8.6 × 103) (2.2 × 103) (6.8 × 103) (9.9 × 103) (2.0 × 101) (2.9 × 102) 2 2 2 0 1 −1∗ 1.4 × 10 1.2 × 10 2.9 × 10 3.7 × 10 2.0 × 10 dsrBtranscriptsmL 0 0 (1.5 × 102) (7.0 × 101) (1.8 × 102) (1.6 × 100) (9.0 × 100) 0 1 2 1 −1∗ 7. 5 × 10 5.4 × 10 4.6 × 10 2.5 × 10 mcrA copies mL 0 0 0 (2.5 × 100) (2.7 × 101) (5.2 × 100) (4.8 × 100) −1∗ mcrAtranscriptsmL 0000000 NA: data not available. ∗ Figure in brackets shows standard error of mean (SEM). container. The samples were analysed within 2 days of sampl- 2.4.TotalCellCounts. The total number of cells (TNC) was 󸀠 ing. determined by fluorescent staining with 4 ,6-diamidino-2- phenylindole (DAPI) [21]withslightmodifications.A5mL 2.3. Geochemistry. The geochemical data were provided by subsample of each groundwater sample was stained with −1 Posiva Oy and are presented in Table 1.Measurementswere DAPI (1 𝜇gmL ) for 20 min at room temperature in the dark performed as described in Table 2. and collected on black polycarbonate Isopore Membrane 4 BioMed Research International

Olkiluoto Location of the boreholes sampled for microbial analysis Coordinate system: Finnish coordinate system, zone 1 24.2.2012 Saanio and Riekkola Oy, KF

(m) KR1 0 250 500 Core drilled borehole

Figure 1: Map of Olkiluoto area where the different boreholes sampled in this study are indicated as open triangles. The arrows show the direction in which the boreholes lead. The scale bar is equal to 500 m. filters (0.2 𝜇m GTBP, Millipore, Ireland) with the Millipore isolation. Negative isolation controls were performed from 1225 Sampling Manifold (Millipore, USA) under low vacuum. clean cellulose-acetate filter units in parallel with the samples The filters were rinsed with 1 mL filter sterilized 0.9% NaCl usingthesameprotocolandreagentsasforthesamples. prior to and after filtration. Fluorescent cells were visualized Residual DNA in the RNA extracts was checked by PCR under UV light with an epifluorescence microscope (Olym- with the primers used in this study (Table 3). If no PCR pus BX60, Olympus Optical Ltd., Tokyo, Japan) and 1000x productwasobtained,itwasassumedthatallresidualDNA magnification. The number of cells was calculated from 30 was successfully removed and the RNA extract was submitted random microscopy fields according to the magnification fac- to cDNA synthesis. If a PCR product was obtained, the tor,filteredvolume,andthesurfaceareaofthefilterused[22]. RNA extract was treated with DNase (Promega, WI, USA) according to the manufacturer’s instructions. cDNA was 2.5. Nucleic Acid Isolation. Microbial community nucleic synthesized by first incubating 11.5 𝜇L aliquots of RNA extract acids (DNA and RNA) were isolated directly from the frozen together with 250 ng random hexamers (Promega, WI, USA) cellulose-acetate filters with the PowerSoil DNA or Power- and 0.83 mM final concentration dNTP (Finnzymes, Espoo, ∘ Water RNA extraction kit (MoBio Laboratories, Inc., Solana Finland) at 65 C for 5 minutes before cooling the reactions Beach, CA), respectively. Filters for DNA extraction were cut on ice for 1 minute. The reverse transcription was then into 2 × 2 mm pieces with sterile scalpels in a laminar flow performed with the Superscript III kit (Invitrogen), by adding hood before insertion into the lysis tube. Nucleic acids were 4 𝜇L 5x First strand buffer, 40 U DTT, and 200 U Superscript isolated according to the manufacturer’s instructions except III to the cooled reactions. To protect the RNA from degra- that for DNA extraction, the microbial cells were lysed by dation, 40 U of recombinant RNase inhibitor, RNaseOut bead beating with a Precellys (Bertin Technologies, France) (Promega, WI, USA), was used. The reactions were incubated ∘ ∘ ∘ homogenizer for 30 s with 5 s increments at room tempera- at 25 Cfor5minutes,50Cfor1h,and70Cfor15min. ture.TheDNAandRNAfrom500mLand1000mLsamples Three parallel reactions were performed for each sample as were eluted in 50 𝜇Lelutionbufferand100𝜇Lelutionbuffer, well as for the reagent controls. The parallel reactions were respectively. Three replicate filters were used for DNA or RNA subsequently pooled. BioMed Research International 5

Table 2: Geochemical analysis methods and the detection limit of each assay used in this study. The data were obtained from Posiva Oy.

Parameter Unit Method Detection limit pH pH meter, ISO-10532 −1 EC (mS m ) Conductivity analyzer, SFS-EN-27888 5 TC: 0.6 −1 NPOC (mg L ) SFS-EN 1484 IC: 0.3 l TOC: 0.3 −1 TDS (mg L ) −1 Alk (meq L ) Titration with HCl 0.05 2− −1 SO4 (mg L ) IC, conductivity detector 0.1 − −1 S2 (mg L ) Spectrophotometry 0.1 − −1 NO3 (mg L ) FIA method, SFS-EN ISO11905-1 0.05 + −1 NH4 (mg L ) Spectrophotometry, SFS 3032 −1 Fe2+ (mg L ) Spectrophotometry 0.01 −1 Na2+ (mg L ) 2007: FAAS, SFS3017, 3044 5 2008: ICP-OES 0.5 −1 K+ (mg L ) 2007: FAAS, SFS3017, 3044 0.31 2008: ICP-OES 0.5 −1 Ca2+ (mg L ) 2007: FAAS, SFS3017, 3044 0.02 2008: ICP-OES 0.1 −1 Mg2+ (mg L ) 2007: FAAS, SFS3018 0.15 2008: ICP-OES 0.02 − −1 Cl (mg L ) Titration 5 −1 −1 CH4 (mL L gas) Gas chromatography 1 𝜇LL gas

Table 3: The primers used for amplification of different microbial groups for 454 pyrosequencing. The archaeal 16S rRNA andthe mcrAgene transcripts were amplified using a nested PCR approach.

Fragment length (gene Target Primer Sequence Reference location) ∗ 󸀠 󸀠 8F 5 -AGAGTTTGATCCTGGCTCAG-3 ca. 500 bp [23] Bacteria 16S rRNA ∗ 󸀠 󸀠 P2 5 -ATTACCGCGGCTGCTGG-3 (V1–V3) [24] 󸀠 󸀠 A109f 5 -ACKGCTCAGTAACACGT-3 [25] 󸀠 󸀠 ca. 800 bp Arch915R 5 -GTGCTCCCCCGCCAATTCCT-3 [26] Archaea 16S rRNA ∗ 󸀠 󸀠 ARC344f 5 -ACGGGGCGCAGCAGGCGCGA-3 ca. 430 bp [27] ∗ 󸀠 󸀠 Ar744r 5 -CCCGGGTATCTAATCC-3 (V3-V4) modified from [28] 󸀠 󸀠 mcrA412f 5 -GAAGTHACHCCNGAAACVATCA-3 [3] 󸀠 󸀠 1.2 kb Methanogens mcr1615r 5 -GGTGDCCNACGTTCATBGC-3 [3] ∗ 󸀠 󸀠 mcrA ME1 5 -GCMATGCARATHGGWATGTC-3 [31] ∗ 󸀠 330 bp ME3r TGTGTGAAWCCKACDCCACC-3 modified from [31] ∗ 󸀠 󸀠 Sulphate reducer 2060F 5 -CAACATCGTYCAYACCCAGGG-3 [29] ∗ 󸀠 󸀠 370 bp dsrB dsr4R 5 -GTGTAGCAGTTACCGCA-3 [30] 󸀠 Primers marked with ∗ were equipped with adapter and barcode sequences at the 5 ends, except if they were used for RT-qPCR. Primers marked with § were used in the qPCR without the adapters and barcodes.

2.6. Amplicon Library Preparation. Libraries for 454 high- fragments were amplified in a single round PCR with tagged throughput (HTP) amplicon sequencing were prepared by primers 2060F [29]anddsr4R [30]. McrA fragments were PCR from the cDNA samples. Bacterial 16S rRNA fragments obtained by nested PCR. Initially, a 1.2 kb mcrAfragment covering the V1–V3 variable regions were amplified with was amplified with primers mcrA412f and mcr1615r [3]. The primers 8F and P2 equipped with adapter and MID sequences product of this PCR was then amplified with tagged primers 󸀠 at their 5 end in a single round PCR (Table 3)[23, 24]. ME1 and ME3r modified from [31]. PCRs were performed Archaeal 16S rRNA fragments were produced with a nested with Phusion DNA polymerase (Finnzymes, Espoo, Finland) PCR using primers A109f and Arch915R [25, 26]forthefirst in 1x HF buffer. Each 50 𝜇L reaction contained 0.5 mM round and tagged primers ARC344f and Ar744r [27, 28] dNTP and 1 𝜇Mofprimers.ThePCRconditionsconsisted ∘ covering the V3-V4 variable areas for the second round. DsrB of an initial denaturation step of 30 s at 98 C, followed by 6 BioMed Research International

∘ ∘ ∘ 35 cycles of 10 s at 98 C, 15 s at 55 C, 15 s at 72 C, and a eight nucleotide long homopolymer stretches, and defined ∘ final extension step at 72 C for 5 min. Two replicate samples minimum length). The minimum length was 300 bp for wereusedforeachboreholedepthandaminimumoftwo bacterial 16S rRNA and dsrBsequencesand200bpfor amplification reactions were performed for each replicate archaeal 16S rRNA and mcrA sequences. The bacterial and sample, which were subsequently pooled prior to sequencing. archaeal 16S rRNA sequences were aligned with Mothur All PCR reactions were also run with the negative nucleic [32]usingaSilvareferencealignment[33]forbacterial acid extraction and reagent controls. The sequencing was (14 956 sequences) and archaeal (2 297 sequences) 16S performed at the Institute of Biotechnology, University of rRNA gene sequences, respectively. The dsrBsequenceswere Helsinki, Finland, using the FLX 454 (454 Life Sciences, aligned with Geneious Pro (v 5.6, Biomatters Ltd., New Branford, CT, USA). Zealand) using a dsrAB model alignment [34] (97 sequences). The mcrA sequences were aligned with Mothur using a 2.7. Real-Time Quantitative PCR. The abundance of bacterial mcrA gene sequence model alignment (this study) (213 dsrBandarchaealmcrA genes and transcripts was deter- sequences). The alignments from the amplicon libraries were mined by qPCR with KAPA SYBR Fast 2x Master mix for checked and manually corrected with Geneious Pro before Roche LightCycler 480 (Kapa Biosystems, Inc., Boston, MA, further analysis with Mothur. USA). Reactions were performed in triplicate for each sam- The sequences were divided into operational taxonomic ple. Each reaction contained 1 𝜇L of extracted DNA or cDNA units (OTUs) based on 97% sequence homology for the as template and 5 pmol of both forward and reverse primers bacterial and archaeal 16S rRNA sequences and the dsrB (Table 3). The qPCR was performed on a Roche LightCycler sequences and 99% for the mcrA sequences. The sequencing 480 (Roche Applied Science, Germany) on white 96-well coverage was evaluated by rarefaction analysis and the esti- plates (Roche Applied Science, Germany) sealed with trans- mated species richness and diversity indices were calculated parent adhesive seals (4titude, UK). The qPCR conditions ∘ in Mothur. consisted of an initial denaturation at 95 Cfor10minutes ∘ The bacterial and archaeal 16S rRNA sequences were followed by 45 amplification cycles of 15 seconds at 95 C, 30 ∘ ∘ taxonomically classified with Mothur using the GreenGenes seconds at 55 C, and 30 seconds at 72 Cwithaquantification 13 8database[35]. The representative sequences of the measurement at the end of each elongation. A final extension dsrBandmcrAOTUswereanalysedusingtheGeneious ∘ step of three minutes at 72 C was performed prior to a Pro (Biomatters Inc., New Zealand). The dsrBandmcrA melting curve analysis. The melting curve analysis consisted sequences were imported into Geneious Pro and aligned ∘ of a denaturation step for 10 seconds at 95 Cfollowedby to reference sequences and most closely matching sequences ∘ an annealing step at 65 C for one minute prior to a gradual determinedagainsttheNCBIdatabasewithblastntool ∘ ∘ −1 temperature rise to 95 Catarateof0.11Cs during which in Geneious Pro. The alignments were performed with the fluorescence was continuously measured. The number Muscle [36] using default settings and the alignments of gene and transcript copies was calculated by comparing were edited manually. The mcrAanddsrBsequenceswere the amplification result (Cp) to that of a dilution series of subsequently translated to amino acid sequences before plasmids containing mcrAordsrB genes ranging from 0 to phylogenetic analyses. Phylogenetic analyses were performed 7 10 gene copies per reaction as described in Nyyssonen¨ et on the alignments using PhyML [37]withtheJukes-Cantor al. [3]. The lowest detectable standard concentration for the (JC69) [38] substitution model for nucleic acid sequences and dsrBqPCRwas16dsrBgenecopies/reaction.InthemcrA the Whelan-Goldman substitution model [39]foraminoacid qPCR assay, the lowest detectable standard had 100 mcrA sequences. Bootstrap support for nodes was calculated based copies/reaction. Template inhibition of the qPCR was tested on 1000 random repeats. 4 by adding 2.17 × 10 plasmid copies containing fragment of For comparable 𝛼-and𝛽-diversity analyses the data sets the morphine-specific Fab gene from Mus musculus gene to were normalized by random subsampling according to the reactions containing template DNA or cDNA and comparing samplewiththelowestnumberofsequencereads,thatis, the result to a dilution series of the plasmid as described in [3]. 1200,893,2249,and2324sequencesforarchaea,bacteria, TheinhibitionoftheqPCRassaybythetemplateDNAwas dsrB, and mcrA, respectively. foundtobelow.TheaverageCrossingpoint(Cp)valueforthe The sequences have been submitted to the Euro- 4 standard sample (2.17 × 10 copies) was 28.7 (±0.4 std), while pean Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena/) for the DNA samples the Cp was 28.65–28.91 (±0.03–0.28 std) under accession numbers ERS514153–ERS514176. and for the cDNA samples was 28.69–28.96 (±0.02–0.23 std). Nucleic acid extraction and reagent controls were run in all 2.9. Statistical Analyses. Statistical analyses were calculated qPCRs in parallel with the samples. Amplification in these with PAST v. 3.0 [40] in order to determine which of controls was never higher than the background obtained these parameters correlated most strongly with the detected fromthenotemplatecontrols. taxa. The Shapiro-Wilk test [41] and Anderson-Darling test [42] were performed to analyze the normal distribution of 2.8. Sequence Processing and Analysis. Sequence reads were the geochemical parameters. For sample parameters with trimmedwithMothur(v1.31.2)[32] to remove adapter, 𝑃 < 0.05 normal distribution were rejected and these para- barcode, and primer sequences and to exclude sequences meters were excluded from the correlation calculations. that did not meet the quality criteria (i.e., no barcode and The excluded parameters were DIC, bicarbonate, alkalinity, primer mismatches, no ambiguous nucleotides, maximum sulphate, Stot,Ntot, Fe(II), Ftot, Sr, 16S rRNA gene copies BioMed Research International 7

−1 −1 −1 mL ,anddsrB transcripts mL and mcrA genes mL . obtained. Transcripts of the mcrA genes were obtained for Pearson’s linear 𝑟 correlation between presence and absence 454sequencingwithnestedPCRamplificationfromfour of different taxa in correlation to the geochemical parameters different depths, 328 m, 347 m, 572 m, and 798 mbgsl (Figure was calculated with PAST. 7). The mcrA transcripts belonged to four methanogenic genera (Figure 8) that covered the Chao1 estimation of the 3. Results and Discussion total mcrAdiversity. Diversity of the active microbial communities was highest The crystalline bedrock of Olkiluoto has been chosen to at sampling depths between 296 and 347 mbgsl, that is, in the 󸀠 host the deep geological repository for spent nuclear fuel SMMZ. At this depth, both bacterial diversity (𝐻 =1.8, in Finland. The spent nuclear fuel will be stored in copper normalized to equal number of sequence reads/sample) and 󸀠 canisters with nodular cast iron insert at 450 m depth and SRB (𝐻 =2.29and 2.65) diversity were the highest (Table 󸀠 isolated from the bedrock by bentonite clay. Groundwater 4). The highest archaeal diversity𝐻 ( = 1.91), in contrast, salinity and carbon content at different depths as well as the was seen in the lowest boundaries of the SMMZ at 347 mbgsl. increase in the amount of CH4 and H2Sanddecreasein 2− The diversity of the methanogenic communities was low inall the amount of SO4 at specific depths suggest the existence samples from which sequences were obtained by nested PCR 󸀠 of a broad sulphate-methane mixing zone (SMMZ) in the (𝐻 = 0.42–0.76). groundwater at approximately 250–350 mbgsl depth [2]. At corresponding sulphate-methane transition zones (SMTZ) 3.1. Sulphate-Methane Mixing Zone (SMMZ). The structure in marine sediments both the microbial activity and the of the active bacterial communities was similar between diversity of the microbial communities increase dramatically samples derived from similar depth of the different boreholes [9, 43].Ifthesamekindofintensifiedactivityoccursin but changed with greater depth intervals (Figure 2). Sampling groundwater SMMZs an increased risk may arise for, for depths between 296 and 347 mbgsl contain the most H2S 2− example, microbially induced sulphate reduction aided cor- and SO4 rich water in this study and are influenced by rosion of the waste capsules, release of radioactive waste, and a fraction of the methane-rich groundwater from deeper mobilization of radionuclides. groundwater layers. Here, the most abundant bacterial group In this study, we investigated the transcriptionally active was 𝜀-proteobacteria of the Helicobacteraceae family mostly microbial communities of the deep methane-rich groundwa- belonging to the Sulfurimonas.Thisgroupformed54–95% ter spanning the depth of the future spent nuclear fuel repos- of the active bacterial communities as determined by the itory. Triplicate groundwater samples from depths between total number of sequences. 𝜀-proteobacteria are believed to 296 and 798 mbgsl from seven different boreholes in Olkilu- be enriched in the vicinity of SMTZs in marine sediments oto were collected in order to characterize the active micro- [44] and many are mesophilic, H2- and sulphur-oxidizing bial communities around the depth of the planned repository chemolithoautotrophs [44–46]. They may play a profound 2− 2− (Table 1, Figure 1). The samples represented brackish SO4 role in recycling H2StoSO4 and are also a significant group rich water and saline methane-rich water (as classified in in SMMZ microbial communities [10]wheretheyfixCO2 at [2]). The carbonate content in the groundwater generally the expense of sulphides and other electron donors. By fixing decreased with depth whereas in deeper water the concen- CO2,theymayaccountforasignificantamountofassimilated tration of methane increased from almost none at 296 m to −1 carbon compounds available to microbial communities in more than 900 mL L gas at 800 mbgsl. The concentration of deep subsurface environments [47]. The second largest group 2− −1 SO4 was highest (379 mg L groundwater) in the sample at 296–347 mbgsl was Desulfobacterales 𝛿-proteobacteria from 328 mbgsl and decreased radically with depth. The forming2–29%oftheactivecommunitybasedon16SrRNA H2S concentration was also highest at 296–347mbgsl and (Figure 2). This is in accordance with the detection of the decreased with depth. dsrB gene transcripts similar to uncultured group 1 Desul- −1 The TNC mL groundwater varied between 4.2 × fobulbaceae of the Desulfobacterales family at this depth. 5 −1 4 −1 10 mL at 296 m and 1.5 × 10 mL at415mbgslwitha These dsrB transcripts formed more than 69% of the dsrB general decline with depth (Table 1). HTP sequencing of bac- transcripts at 296 mbgsl and showed a positive and significant terial and archaeal 16S rRNA with 454 technologies identified correlation (>0.8, 𝑃 < 0.01) with pH between 7.9 and 8.1. a total of 95 bacterial families and 27 archaeal families in the At 328 mbgsl, dsrB transcripts of the genera Desulfotignum seven analyzed samples (Figures 2 and 3). The rarefaction and undefined Desulfosarcina of the Desulfobacteraceae were analyses showed that the bacterial and archaeal communities the most common. The amount of dsrB genes varied between 4 −1 were well characterized from 415 to 572 mbgsl (Figure 4). 0.5 and 3.1 × 10 copies mL at 296–374 mbgsl. In addi- In the remaining samples, between 16 and 52% of the tion, the highest transcriptional activity of the dsrB genes, 2 −1 estimated bacterial and archaeal OTU richness was captured 1.2–2.9 × 10 transcripts mL , was detected here, coincid- by sequencing. ing with the highest sulphate and sulphide concentrations dsrB gene transcripts were obtained from sequencing and the lowest methane concentrations measured in this from depths between 296 mbgsl and 572 mbgsl, but not from study. the deepest sample from 798 mbgsl. The dsrBsequences At 296–347mbgsl, a minor portion of the bacterial com- belonged to six different SRB families and 14 genera (Figures munity belonged to methylotrophic 𝛽-proteobacteria and 5 and 6). The dsrB transcript diversity was well covered show- Verrucomicrobia, which may be capable of methane oxida- ing between 81 and 98% of the estimated Chao1 OTU richness tion in the SMMZ (Figure 2). However, a more likely scenario 8 BioMed Research International 0.09 m m m m m m m 296 798 572 559 415 347 330 0.095 Unclass. Bacteria 0.095 0.284 C111 Acidimicrobiales 0.095 Unclass. Actinomyvtales 0.379 ACK-M1 0.095 Brevibacteriaceae 3.602 Corynebacteriaceae 0.095 Dermacoccaceae 0.095 Frankiaceae Actinomycetales Actinobacteria Actinobacteria 0.095 Kineosporiaceae 2.749 0.947 16.004 0.473 0.095 Microbacteriaceae 18.294 0.189 0.189 Micrococcaceae 0.095 4.830 0.189 0.095 Nocardiaceae 2.844 0.095 0.095 Propionibacteriaceae 3.409 OPB41 0.189 Armatimonadaceae Armatimonadales Armatimonadia Armatimonadetes 0.095 Porphyromonadaceae 0.190 Paraprevotellaceae Bacteroidales Bacteroidia 0.189 0.095 Unclass. Bacteroidetes Bacteroidetes 0.095 Cytophagaceae Cytophagales Cytophagia 0.095 0.095 0.379 Weeksellaceae Flavobacteriales Flavobacteriia 0.095 0.095 Chitinophagaceae Saprospirales Saprospirae 0.095 BHI80-139 0.095 Caldilineaceae Caldilineales Anaerolineae 0.095 Roseiflexales Chloroflexi Chloroflexi 0.189 0.379 0.189 Dehalococcoidaceae Dehalococcoidales Dehalococcoidetes 0.284 SL56 1.231 Streptophyta Chloroplast 0.095 ML635J-21 Cyanobacteria 0.379 Nostocaceae Nostocales Nostocophycideae 0.190 1.042 Rivulariaceae Stigonematales 0.284 Elusimicrobia 0.095 FBP 46.256 0.095 Staphylococcaceae Bacillales 0.095 Planococcaceae 0.095 Gemellaceae Gemellales 0.095 Aerococcaceae Bacilli 0.758 Carnobacteriaceae 0.284 Enterococcaceae Lactobacillales 0.190 Lactobacillaceae 2.464 0.095 Streptococcaceae 0.095 Unclassified Clostridiales Firmicutes 0.095 0.095 Acidaminobacteraceae 0.190 0.095 Clostridiaceae Clostridiales 0.095 0.189 Eubacteriaceae Clostridia 3.504 Peptococcaceae 3.981 0.284 Tissierellaceae 1.420 Desulforudales 0.095 Natranaerobiales 0.473 Erysipelotrichaceae Erysipelotrichales Erysipelotrichi 0.095 Fusobacteriaceae Fusobacteriales Fusobacteria Fusobacteria 0.189 Victivallaceae Victivallales Lentisphaeria Lentisphaerae 0.095 ABY1 OD1 0.095 0.095 OP3 0.189 0.095 SB-45 JS1 OP9 0.095 SHA-43 Phycisphaerae Planctomycetes 0.379 0.284 1.894 0.095 0.189 0.189 Caulobacteraceae Caulobacterales 0.190 0.095 2.557 0.095 Bradyrhizobiaceae 0.189 Hyphomicrobiaceae 0.190 0.189 Methylobacteriaceae Rhizobiales 0.095 Rhizobiaceae 0.190 Rhodobiaceae Alphaproteobacteria 1.989 Rhodobacteraceae Rhodobacterales 0.569 Acetobacteraceae Rhodospirillales 0.190 0.095 0.284 0.095 mitochondria Rickettsiales 0.095 Unclass. Sphingomonadales 0.095 Erythrobacteraceae Sphingomonadales 1.422 3.504 0.947 0.758 0.095 0.095 0.379 Sphingomonadaceae 0.095 Unclass. Burkholderiales 0.095 0.568 14.773 3.409 0.095 0.284 0.284 Comamonadaceae Burkholderiales 1.043 Oxalobacteraceae Betaproteobacteria 0.095 Methylophilales Proteobacteria 0.095 Neisseriaceae Neisseriales 1.799 0.095 1.894 Rhodocyclaceae Rhodocyclales 0.095 0.379 Unclass. Deltaproteobacteria 8.617 1.420 4.545 Desulfobulbaceae Desulfobacterales 0.284 20.170 0.947 0.473 Desulfobacteraceae 0.852 Desulfovibrionaceae Desulfovibrionales Deltaproteobacteria 0.379 Desulfomicrobiaceae 0.189 Pelobacteraceae Desulfuromonadales 0.095 Cystobacterineae Myxococcales 0.189 0.473 0.095 Syntrophaceae Syntrophobacterales 0.095 Campylobacteraceae Campylobacterales Epsilonprot. 0.569 54.545 94.60 86.17 Helicobacteraceae 1.611 Enterobacteriaceae Enterobacteriales 0.095 Pasteurellaceae Pasteurellales Gammaprot. 1.706 Moraxellaceae Pseudomonadales 6.635 94.223 41.572 90.625 8.996 0.947 1.136 Pseudomonadaceae 0.095 0.663 0.095 noFP_H7 AB16 SAR406 3.598 MVP-15 0.758 3.409 PL-11B10 MVP-15 Spirochaetes 0.095 Spirochaetaceae Spirochaetales Spirochaetes 0.663 0.095 Acholeplasmataceae Acholeplasmatales Mollicutes Tenericutes 1.327 Deinococcus Thermi 0.095 0.473 EW055 TM7-3 TM7 0.095 Verrucomicrobia

Figure 2: The relative distribution of bacterial 16S rRNA sequence reads belonging to specific bacterial families. The relative abundance of sequence reads are highlighted by color, where green represents the lowest relative abundance, yellow represents medium abundance, and red represents high abundance. The samples were clustered using the Morisita-Horn algorithm in Mothur. The data were normalized between the different samples to include 893 random sequence reads from each sample. BioMed Research International 9

Crenarchaeota Euryarchaeota

Methanomicrobia Thermoplasmata Halobacteria Methanopyri Thermoprotei Methanobacteria ANME-1 Sulfolobales Halobacteriales Methanopyrales Methanosarcinales Methanomicrobiales Thermoplasmatales Methanobacteriales Sulfolobaceae DSHV_Gp_6 Methanobacteriaceae Methanothermaceae Methanobacteriaceae ANME-1a Methanoregula uncultured GOM_Arc_I Methanosarcinaceae Methanosarcinaceae Methermicoccaceae Methanopyraceae 20c-4 AMOS1A-4113-D04 BSLdp215 KTK_4A TMG C3 MBGB MCG pMC2A209 pSL1 AK5 D-C06 SAGMEG MBGE 296 m 1.91 0.08 1.19 0.48 0.16 1.27 0.24 1.11 0.08 0.88 3.10 0.48 0.16 0.08 12.65 9.63 66.35 318 m 0.48 0.95 3.10 0.08 1.35 0.08 76.77 17.18 347 m 0.40 0.24 2.39 0.24 0.80 0.40 2.47 0.24 0.16 0.16 37.79 31.11 23.55 415 m 0.08 0.08 0.80 0.08 0.16 0.64 1.03 0.32 0.08 0.24 0.24 0.40 1.83 50.52 29.75 13.76 559 m 0.08 0.08 0.56 2.86 0.16 4.14 0.40 0.16 7.24 0.56 1.35 0.32 80.27 1.83 572 m 0.08 0.80 1.03 0.08 3.02 0.32 6.92 1.35 0.40 69.85 16.15 798 m 0.08 0.2 67.06 32.86

Figure 3: The relative distribution of archaeal 16S rRNA sequence reads belonging to specific archaeal families. The relative abundances of sequence reads are highlighted as described in Figure 2. The samples were clustered as described in Figure 2.Thedatawasnormalized between the different samples to include 1200 random sequence reads from each sample. for methane oxidation is the AOM process performed by 3.2. Methane-Rich Groundwater. Below the SMMZ, at 415– archaeal ANME linages. Nyyssonen¨ et al. [3]reportedputa- 572 mbgsl, the sulphate concentration in the groundwa- tive ANME-1 mcrA genes from the 300 to 400 mbgsl in ter is greatly reduced, the groundwater salinity increased, Olkiluoto. In the present study, the active archaeal communi- and the methane concentration is high. At this depth, 𝛾- ties detected in the SMMZ mainly consisted of GOM Arc I proteobacteria most similar to Pseudomonas species dom- Methanosarcinales (Figure 3), which also are known as the inated (41–94%) the active bacterial communities. These ANME-2D. ANME-2D archaea have been shown to indepen- bacteria may be the major CO2-fixing bacteria in Olkiluoto dently perform nitrate mediated AOM without the need for deep methane rich groundwater, as they have been shown to abacterialpartner[48].ThisisinagreementwiththemcrA be in the Baltic Sea [50]. gene transcripts detected at this depth, which mostly (55– Apeakinthebacterialdiversitywasseenat559mbgsl 100%) belonged to Methanosarcinales groups. in the methane-rich groundwater. Several SMTZ signature At the lower boundaries of the SMMZ at 347 mbgs, groups were detected at this depth including putatively the active SRB community changed and the dsrBgene methylotrophic 𝛼-and𝛾-proteobacteria, 𝛽-proteobacteria, transcript pool was dominated by transcripts belonging to 𝛿-proteobacterial SRB, JS1, Actinomycetes, Planctomycetes, an uncultured Desulfobacteraceae group of SRB most closely and Chloroflexi. 𝛽-proteobacteria belonging to the Burkhol- related to Desulfobacter (86.5%), overlapping the distribution deriales, for example, are believed to be the sole bacterial of ANME-1 in Olkiluoto. Desulfosarcina dsrB transcripts partner performing nitrification in the AOM association were found only at low abundance but were most numer- with ANME-2c archaea [51]. 𝛽-proteobacterial families Sph- ous at 296–328 mbgsl. Together with the Desulfobacter the ingomonadaceae and Comamonadaceae were detected as Desulfosarcina also belongs to the Desulfobacteraceae. These minority (<3.5%) at all depths. 𝛽-proteobacteria were a major Desulfosarcina have been reported to form AOM consortia group only at 559 mbgsl where Acidovorax sp. (Comamon- with ANME-1 and ANME-2 archaea [49], which may indicate adaceae) contributed almost 15% of the active community that these associations also occur in Olkiluoto groundwater and correlated positively and significantly with the highest SMMZ. pH measured in the present study. A low abundance (<1%) 10 BioMed Research International

Bacteria Archaea 120 90 80 100 70 80 60 50 60 40 40 30 Number of OTUs of Number Number of OTUs 20 20 10 0 0 1 1 50 55 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 110 165 220 275 330 385 440 495 550 605 660 715 770 825 880 935 990 1000 1050 1045 1100 1155 1210 Sequence reads Sequence reads (a) (b) dsrB mcrA 60 20 18 50 16 14 40 12 30 10 8 20 Number of OTUs of Number Number of OTUs of Number 6 4 10 2 0 0 1 1 525 630 735 840 945 105 210 315 420 100 200 300 400 500 600 700 800 900 1050 1155 1260 1365 1470 1575 1680 1785 1890 1995 2100 2205 2310 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 Sequence reads Sequence reads 296 m 559 m 296 m 559 m 328 m 572 m 328 m 572 m 347 m 798 m 347 m 798 m 415 m 415 m (c) (d)

Figure 4: Rarefaction curves of the sequence data obtained from each RNA extract normalized to equal number of sequence reads per sample: (a) bacterial 16S rRNA, (b) archaeal 16S rRNA, (c) dsrBtranscripts,and(d)mcrAtranscripts.The𝑥-axis displays the number of sequence reads and the 𝑦-axis displays the number of different OTUs obtained. Figures (a)–(c) present rarefaction values at the distance 0.03 and (d) rarefaction for distance 0.01.

of methanotrophic 𝛼-proteobacterial Methylobacteriaceae most abundant archaea at 559 mbgsl (80.3%) and terrestrial (Methylobacter sp. and Methylocystis sp.) correlating signif- miscellaneous group (TMG) Thermoplasmatales at 572 mbgsl icantly with depth and salinity were found at this depth. (69.9%). Nevertheless, the mcrA transcripts at 572 mbgsl Similar methanotrophs have readily been isolated from mostly (75%) belonged to Methanobacteriales methanogens. anaerobic methane-rich deep subsurface environments, such ANME-1 archaea were found in the methane-rich ground- as terrestrial mud volcanoes [52]. Wrede et al. [52]suggested water at 415 and 559 mbgsl (4.1% and 1.0%, resp.) and cor- that aerobic methane oxidation could be activated whenever related positively although not significantly with the highest oxygen was available and thereby keep the subsurface ecosys- pH values measured in this study. ANME-1 archaea were tem anaerobic. most abundant at depths where the GoM Arch I/ANME-2D Methylotrophic Methermicoccaceae and SAGMEG Ther- archaea were mainly absent. Recent research shows that some moplasmata were the most abundant archaea at 415 mbgsl ANME groups are capable of performing sulphate mediated (50.5% and 29.8%, resp.). Hydrogenotrophic Methanobac- AOMontheirown[53], where they form S2 by a so far 2− teriaceae, which correlated with the highest pH, were the unknown sulphate reduction process. The 4SO -mediated BioMed Research International 11

Deltaproteobacteria Clostridia Clostridiales

Desulfobacterales Desulfovibrionales Thermoanaerobiales Peptococcaceae

Desulfobacteraceae Desulfobulbaceae Desulfomicrobiaceae Thermodesulfobiaceae Desulfotignum Desulfobacter Desulfofaba Desulfatibacillum Desulfosarcina Desulfosarsina Undefined 1 Unclassified Desulfotalea Desulfobulbus 2 Unclassified Desulfomicrobium Desulfotomaculum Uncultured Unclassified 296 m 0.88 0.92 3.70 1.32 0.18 0.22 6.51 0.48 5.55 69.10 11.14 328 m 1.50 0.04 0.04 0.09 0.66 1.06 0.62 0.13 3.26 39.96 10.34 42.30 347 m 0.48 0.22 0.35 0.31 4.31 6.21 0.09 0.09 0.57 0.44 0.09 86.58 0.26 415 m 0.92 0.13 0.35 0.09 0.35 7.13 0.57 0.18 0.40 89.88 559 m 0.31 0.35 1.72 0.79 0.22 76.80 13.64 6.16 572 m 0.48 1.45 0.09 0.92 0.09 0.09 15.23 32.83 19.85 28.96 Figure 5: The relative distribution of dsrB transcript sequence reads belonging to specific SRB families according to the phylogenetic identification of the sequences presented in Figure 6. The relative abundance of sequence reads and the clustering of the samples are presented as described in Figure 2. The data were normalized between the different samples to include 2249 random sequence reads from each sample.

AOM performed by the ANME-1 could dominate specifi- these sulphate reducers were abundant in the methane rich cally at 415–559 mbgsl, where the concentration of methane andsulphatepoorgroundwater.At415mbgslDesulfotomac- increases dramatically. Our results are similar to those of ulum dsrB gene transcripts were the most abundant (89.9%) Pedersen [54], who suggested that a sulphate mediated AOM while Desulfobulbaceae family 1 of the Desulfobacterales process coupled to sulphate reduction may occur in Olkiluoto dominated(76%)at559mbgslandshowedpositiveand groundwater at the SMMZ depth, although they did not significant correlation with pH the highest groundwater pH. obtain conclusive evidence for this process. The most even distribution of dsrB gene transcripts was seen In the methane-rich water, the methanogens and SRB at 572 mbgsl, where Desulfatibacillum (>32%), Desulfomicro- were clearly enriched at different depths. At 559 mbgsl where bium (>19%), and uncultured Desulfobulbaceae (uncultured 2 −1 the highest number of mcrA genes (4.6 × 10 copies mL ) 1) (>28%) dominated the SRB communities. Firmicutes dsrB was detected the number of dsrB genes was only 6.5 × gene transcripts other than those belonging to Desulfo- 1 −1 10 copies mL and no dsrB transcripts could be detected tomaculum were detected only at <1% relative abundance at by qPCR. DsrB genes in contrast were abundant above 328 mbgsl and were present at 296–415 mbgsl and 572 mbgsl 4 −1 3 (1.6 × 10 copies mL at 415 mbgsl) and below (2.2 × 10 (Figure 6). These dsrBsequencesallbelongedtoThermod- −1 dsrBcopiesmL at 572 mbgsl) this depth although the sul- esulfovibrio species previously found in soil environments. −1 phate concentration in the water was only 0.5–1.4 mg L .The −1 reason for the higher amount of dsrBgenecopiesmL in the 3.3. Deep Methane-Rich Groundwater. At 798 mbgsl, the sulphate poor water may be that the SRB live by fermentation groundwater is highly saline with over 53 g dissolved solids −1 instead of sulphate reduction. For example, Desulfobulbus L and a high concentration of methane. The microbial com- and Desulfotomaculum species have been shown to reduce munity at this depth was clearly different from those at the Fe(III) during fermentation of pyruvate [55, 56]. Both of other depths. However, the bacterial diversity at this depth 12 BioMed Research International

Desulfofaba G-40 Desulfomicrobium M 28 6 1756 D 46 , es 29 3

s 650 4 u e 717 lfovibri awater aawater 3 O EBext-43, petrol M- 47 , FR87 4 871737 0 utoI_dsr 0 d R8 7 R EF0 n F , FM212301 33 o I-31, sea la e - Desulfosarcina 100 M0 na S in - 52 le Sea,

DB_dsr12, marine aquaculture biofilter, EU350969 err , H FR871 n 7 s 753 M 23 a 1 B_ I-70, Seawater d d, LG 6 ina n

lea a 4 h , Finland, F , Outok WG14, leachate- w 29 an Se luoto, F TopDsr17, River estuarine sediment,a China, c i 212310 oto eum-contaminated sed ter and le ha Finl d, FR87 M- , n 0 NTd-I14, Nankai Trough deep-sea sediment, AB263138 M o

te-p mud, AY East CEast 36157 M-OLKR weg Desul GIB lkilu umpu dee 33 , Olkiluoto, Finland,

er, er, Desulfobotulus ollute bile 415 ater, Olki er M- lkiluot 3 o to, Finla 125 , Nor ter, O at and leach AM2 o fosarcina v I k Berre, F achate polluted gr O w 4 m M- u Desulfonema quif 63 , 347 d J 02 n d groun al 59 Desulfovibrio p b B2 ediment, Etang de B d a 5 ndwa polluted aqu GIB M- ou Desulfurococcus G A u Olkil o 2 r , Groundwo dwater r S re Desulfatibacill 8 r G opic M- tang de U lack Sea, te IYO- h a 3 QAY G a Desulfosarc ated s ole, te I ollute 72 ariabili B oun 4

iment, E dwater polluted J gga Pockmar Gr 197 1 400 01 45 29 10|419 1738 , Deep- te-p ent, Desulfonema limic 7|659 57 ye land, FR871749 nland, HM467430 B 89 _8, _dsrB_2, 87 i

ha groundw – s s ifer ogenic tr AF418190 F 5 2 0615 AF418 c 18 , Fin X 1 N Desulfobo , DQ2 0 o TE 2, tang de Berre, FM212320tr 2, o sea chi 0 edim 3 1| 9 t epth, um , East China undwate 3 AF334593 o

. M lea and, FR ina ce g , s m dept S T -732m 34 B_17, lu D r 19m_dsrB_11, sulfid m_dsrB 9|880 29 A o 5, 5-553m_dsrB_21, e alkenivorans, AY5 o 8, G1 8 um, AB n s De undw 7 PW ul mne Desulfoc ntpel 507 3 o, Finl 01 3 3030 M- DSM 569

furococcus o tonica, G0 arine 00-500m d sulfoce t S h deep-sea sediment, -3 4 gelida luot De ulu h, Fin oleum-contamin 3 m_dsr 08 ns DSM 92 srE0 y, Suiyo L EJ heron r m aminated sediment, E 54 Y r, 330 7 _415-4 3 s sul 3, no t KR43_68 l , p A f Desul o s sapovo ier ater, DQ D 01 n - 419 , , Olki Desulfobacterium ob l l J o - occus multivora Sea, EF065 6 la halo a LGW 4 _2-d 5 la AF420282 Q2 M VT -KR40_54 novora a , 111 OL m a retbaense D M I GGE band ct Seamount,D nd, AF1919 0 41 e fos SM 2076, A FJ748824 3 ai troug -KR49 orale Groundwater, Olki l 100 _ m oge ri eov BSI-4 GJ eep borehole, 50780 100 B k OL um autotp p -24, pet obiu t Desulfotomaculum HM467432 sulfofaba ira ran fg8d OL or hila, AF Nye- roundwater 67429 joe ans H 25078 GI g 4 11, 04 Nan OL-KR47_3 alobiu s De 7 90 leac Desul r , U5 07 , 5 rphicumgensenii, D AF551759 Japan, AB12492 4261 OL-KR8 icrobium ibrio hydr EBex 40.5 h xd3, AF418201 0 m_dsrB_14, a 4 5 63 9 7 te fob 182 ns, U581Y626031812 38 1 1 8 7 4 , Outokumpu d -po -I01 75 llut act 00 8 DesulfomicrDesulfohtronov _3 0 99.7 er 83 Td 68 F49283 AJ24977 m depth, Finland, HM ed A S 62 029 DB_ vi M 53 A 500 N Desulfom 9_415-4 Desu brio 3382, AF4 I_dsrB 00– ds quif 26 70 ulfona 4 r164 formis, AJ2 5 s N2- er, E lf EBext-33, petroleum-c e Outo 769 , marin DSR-7 obacter latus 9 D as 99. OL-KR4 Desulfotign e aq t China 8 s, AF271 8, o 18 2 OL-KR43_68-73m_dsrB_3,vibrio desulficans, uacul il field 50472182 oran 67 Desulfobacula um balticumtur Sea, EF, U58 e biofi w Desulfoomaculum sp. Srb55, AB260069osapov A3- at 0 124 ulfovibrio aespoeensis, 9, Outokumpu deep borehole, 101580 6M DSR-8, oil field walter er, AB465000 99.8 Des _ aquifer, AY1164Y 29 DSM 7 , EU 88 0 Desulfot frica, A 330M- Desu 93901 5 A 347M- l 044, 35098 50 Desulfotomaculum geothermicum, AF273 415M- fobacula AF 4 OutoI_dsrB hole, South M- GJVT7 toluolica To12ter AJ4571364202 87 Desulfotomaculum therm 2 559 LS01A5 Des , AB49388484 72 57 M- TKG 2|4177 572 ulfob Gold mine bore5|1493 acula phe 76 DC06.4b,-3 3,Columbian River basalt GJVT7LS01 M-559 nolic 66 73 98 SAE5 7 01BFRZX AZN20 8 |1870 57 M-415 a AF551 99. 99 LS 2 55 M-347 758 9 GJVT Nye-0_2-dsrG02, M- 9M-415 M-330M-296 100 mLd4, In situ precipitationnium ofmill heavy tailings metals site, in AY015603 groundwater, AY731421 G11 Nyegga M-347 330 M Pockm a M- M-296 100 58 rk, Norwegian M UMTRAdsr853-36, ura Sea, HM004749 G-89, seawater and leachate polluted groundwater, DQ25076865032 SRB-PM7, anaerob 67 luted aquifer, East China Sea, EF0 ic sludge digestor, FJ535463 LGWG22, leachate pol P2_SRB, anaerobic granular sludge, EU725474 84 Desulforhopalus singaporensis DSM 12130AF418196 ulgidus, M95624 100 Archaeoglobus f DB_dsr8, marine aq Desulforhopalus HM4674279 415M 51 3 uaculture biofilter, EU35096 500 m depth, Finland, 72M-55 M- 65 GIB I4J01DLZBC 21|202 8 400– 02 13|946 5 296M 89 415 4 01EFE 330M- M GJVT7 M 2, Outokumpu deep borehole, GIB3I J M- -330 76 DGGE b LS01A1 OutoI_dsrB_ -347 347M 330M and D26 VAJ 22|92 2 96 -415M 72M- M- UMTRAd num M 87 572 M |590 5 347 5614 93 V09, ber 6, Freshwa anaerobic sludge14|5 blanket bioreactor,15 AY9295982M- 1 0 M 0 GIB sr857 ranDSR4, 09L 3A 57 33 9 99 3 4 Seine -10, ura ter veg G 4 01AZ 4 02HSF 16|283 7M- I J01 estuar nium etated i 3I J 3I J 4 98 EOJDX ntertidal soil, GIB GIB 3IV lings site,3 AY08430 EBext Desulfota y mud mill tailings si 01DF M- 64 D 20| flat, France, AY953 AM18106 3I4J d, FJ -38 esulfot lea psychrophi152 415 te, AY015 6 ium mill|200 tai 572 fiel 5 , pe GIB 17 81 Desu 604 5 tro alea ar M 4 t a uran 9 88 79 8 leum 12 _E8, oil 507, AF337903 74 1 lf Nye-0_2-d cti ater a M46742 4 ofu c la LSv5 01AMBLQ H 195 91 stis -contama, 9 A 4, 7LS Dikom 79 G Y NC entis, AF274767100 7 0 Kalol_C5, o glycolicus D 6260 , groundw S5_89 IB GI sr inate _006 -5 96 Desulf 3 A06, Nyegga 32 GJVT s ATCC 51 10 Desulfobulb I4 B3 d se 138 82 J0 I4 Pelotomaculumenan propionicum,sinus ori AB154391 99 S Mon 1 J01 diment, E g o 4796, AB0778185 , AY62602 97 UIY , e E 8 DSR-O obulbuss elongat Z SM 9705, AF418 UMTRAdsr826 m depth, Finland, m tuar il fi 6 DPN por 2 Pockma 900 halo Y015 00 YH Desulfotalea SM 1 O-10,t2 e tang – A 4 1 53 99 2 ine sedimeld, FJ64842 C 800 hilu 4| S 23|83 29 96 R, acid de te, 58122 6502153093 philum,3 AF418 69 us p rk, N 97431 , 73 5 Desulfos 95 13N Ber U 7 53127 68 51 , lop 1 8 gense gsD si EF0 2631 d ropi orweg re, FM2 8 59 , Y eep-sea 191 M B 6 77 GJVT 40 M tonii AF334599 96 M A vent m onicus,u AF218452nt, F M ian Sea, H 123 A G GJVT -41 ulfitobacterium de 2 F41819 NTd-VII01, Nankai Trough deep-sea sediment, AB263181 OL-KR40_545-553m_dsrB_19,GIB groundwa ine s, AJ310430 M a Sea M DSR- 5 15 nt, DGG I A B J544720 0 Des lows 02 M pu deep borehole, ina, EU25885 e DGGE band 09, leachate-polluted Aquifers, East China Sea, EF064998 7 drainag M- ud, AY7 3 GJVT field, chimE h 0 3 DSR-V, Rainbow vent fie 3 -34 M DSRI- L m mill tailin 3 330 OL-KR40_545-553m_dsrB_20, groundwater, Olkiluoto, Finland, FR871755 bile mud, AY 3 I 7 7 0 m im ment, 4 I S 047 3 334591 - 4 islandicus o 156 0 M utokum d W E J L maculum he le , EF0650 J 1 0 25 di 01 01 ney O M- S -2 ibrio yel oil, C o M 7 5, 11|419 296 se band 23, 01 A 9 M- a, Ra as Desulfotomacul East Chin tomaculum alkali bi Y LS e 6 brio r, , AF B D UKLO b Firmi 47 4, Mari t , Suiyo Seamou H A M srB_ nt URQZ AYN 01 -P i 3 4 415 -18, uraniu 572 W ore Thermodesulfobium5 naru mo e ea se a Sea a opical m 5 s l 0 sulfo n GIB i ci W pica - s site, AY015599 W A mediat 8 i l v nb 9 cutes, paddy S site, fic Rise, OutoI_d |51 a p hi |96 7 d aquife Desulfot fumaroxidans,d 4 V 3 dsr61 rmodesulfov 2 A De e 4 |

ow ven S te a 3 lea 5 1 A 1 ne se 19 4 01 opica t C 27 3 5 I 18|13 |1 L The erm 4 2 87 296 i ermodesulfovi tr chat 6|22 o H |196 | FG LS J 327 5 n ilings 75 572 TU-120,2 7 02 AY354095 , um UMTR Th a n d EU18 35

t O Y obacter DU t, Japan, ime GGZTX e 03 5 A VT lfovirga ough de t fi 3 1 mill tailing M u genic 37 pol chate-pollu 0 ydroth EY 7 4

el 9 GJ h 1 2 7 M m G ld 72 S mill roph do i Tr nt, Denma 17 t 0 M M- L d luted 7 Des fi J on the Mid-A - 6 02 415 M , AB124932 4 Mid-Atlan - J I 5 330 Syn ul nka - s 4 3 5 55 25 n I aquifer, 9 M- B fg7d928, nonsulfidogenic tr 3 9 GJVT uraniu I M- M GWG01, lea , Na , |9 L as Basin 347 M 4 es G

uranium 6 m 02 - 415 -415 GIB rk, A ter, Olkiluoto, Finland, FR871754 4

7, M eral 15 ct M- - M a t E 3

ic M 3-3 ast China 3 M t - lantic Ridge, AY354098 34 0 34 NTd-II lfob Ridge M Desulfobulbus 408822 7 u ng3d1014, no 21, Guay 7 0 M eachate-polluted aquifers, Eas M- l Des TRAdsr624 -330 1P 3

AY35 3 B0 S 0 UM M K13, ea, M- -

MTRAdsr85 29 E 2

U 410 6 96 F065012 M LGW M

0.3

Figure 6: The phylogenetic distribution of the amino acid sequences of the OTUsof dsrB transcripts detected in this study presented as a maximum likelihood tree. The sequences detected in this study are shown in red. Bootstrap support for nodes was calculated with 1000 random repeats and nodes with more than 50% support are indicated. Sequences detected in this study are shown in red. The sequence name codes consist of the sequence IDENTIFIER and the OTU number|the number of sequence reads in that OTU followed by the depths from which this OTU has been detected.

was surprisingly high. The most common bacterial groups the archaeal community consisted mainly of GOM Arc I were the Bacillales and Actinobacteria, which significantly Methanosarcinales/ANME-2D (67%) and TMG archaea increased with increasing depth and salinity throughout (32.9%) (Figure 3). No dsrBormcrA genes or transcripts the studied depth profile and formed 46% and 18% of the were detected by qPCR despite the relatively high microbial 4 −1 activebacterialcommunity.Archaealdiversitywaslow,and density, 2.3 × 10 cells mL . In accordance, no dsrB BioMed Research International 13 Methanosarcinales Methanobacteriales Methanomicrobiales Unclassified Unclassified Unclassified Methanosarcina 296 m

330 m 47.37 52.63

347 m 54.85 45.92

415 m

559 m

572 m 25.49 74.58

798 m 100.00

Figure 7: The relative distribution of mcrA transcript sequence reads belonging to specific methanogenic archaeal families based on the phylogenetic identification of the mcrA reads as presented in Figure 8. The relative abundances of sequence reads are highlighted as described in Figure 2. The data was normalized between the different samples to include 2324 random sequence reads from each sample.

transcripts were obtained for 454 sequencing either. mcrA Overall the active microbial communities in Olkiluoto transcripts were obtained by the nested PCR approach only, deep groundwater are diverse and SRB and methanogens and all sequences belonged to Methanosarcinales methano- are not the only microbial groups to have an influence gens. The coappearance of these mcrA transcripts together on hydrogeochemical conditions and to further be taken with the high relative abundance of GOM Arc IMethano- into account in the safety case of the disposal of spent sarcinales/ANME-2D archaea indicates active methane nuclear fuel. AOM may also be mediated by means other cycling activity of GOM Arc I Methanosarcinales/ANME- than sulphate or nitrate reduction by different bacterial 2D archaea at this depth. groups. The great abundance of bacterial and archaeal taxa generally not involved in methane production or oxidation, 4. Conclusions or nitrate or sulphate reduction, also indicate that the main energy converting metabolic pathways may, in the absence of We observed a clear change in the active microbial com- oxygen, be fermentation of organic molecules. munity composition at the sulphate-methane interface and the methane-rich groundwater in Olkiluoto. Several SMTZ signature groups were detected, as well as a high diversity of Conflict of Interests active microorganisms. We found a characteristic increase in The authors declare that there is no conflict of interests the transcription of the dsrBgeneinthesulphatereducing regarding the publication of this paper. and putative AOM zone between 296 and 347 mbgsl, coin- ciding with mcrA transcripts of methylotrophic methanogens that possibly belong to the ANME-2D. In methane-rich water Acknowledgments between 415 m and 559 mbgsl the ANME-2D were few or absent, while ANME-1 archaea appeared. mcrA transcripts The research project was funded by Posiva Oy, the Academy from an uncultured group of Methanosarcinales archaea of Finland and the Finnish research programme on nuclear cooccurred with the ANME-2D archaea, but whether they waste management (KYT). Mirva Pyrhonen¨ is acknowledged produce or oxidize methane using the reverse methanogene- forskillfulassistanceinthelaboratory.Dr.MichaelHardman sis pathway is not known. is thanked for critical language editing. 14 BioMed Research International

GIB3I4J02H2VGS 3|3679|347M ME_bog75_22, acidic bog, DQ680426 MOBPc433087, marine subsurface sediment, Marennes-Oleron Bay, AM942117 50 60 novmcr1, hypereutrophic lake water, AF525514 L44A, gas condensate-contaminated aquifer, EU364875 mcrA3, hydrothermal vent chimney, Juan de Fuca Ridge, FJ640797 FenG-MCR, oligotrophic fen, AJ489767 Methanomicrobiales BogIII-MCR, drained bog, AJ586243 73 OL-KR42_156-160m_mcrA_14, Olkiluoto groundwater, Finland, FR871723 ME_bog88_30, acidic bog, DQ680423 FenI-MCR, oligotrophic fen, Finland, AJ489769 LMmcrA6, polluted, stratified lake, EF210720 78 ME_bog83_27, acidic bog, DQ680419 92 Methanoculleus palmolei, AB300784 66 Methanoculleus thermophilus, AF313804 Methanogenium organophilum, AB353222 Methanospirillum hungatei JF-1, AF313805 74 Methanocorpusculum parvum, AY260444 Methanospherula palustris E1-9c, EU296536 Methanolinea tarda, AB300466 97 OL-KR42_156-160m_mcrA_12, Olkiluoto groundwater, Finland, FR871722 68 junemcr11, hypereutrophic lake water, AF525524 95 novmcr55, hypereutrophic lake water, AF525522 mcrA_90m_p1_2_TypeC, Lake Kivu hypolimnion, FJ952107 80 mcrA_180m_p1_4_TypeM, Lake Kivu hypolimnion, FJ952121 50 mcrA_180m_p2_10_TypeL, Lake Kivu hypolimnion, FJ952119 88 TopMcrA17, Pearl River estuary sediment, EU681939 93 99 OL-KR40_348-351m_mcrA_77, FR871734 100 OL-KR40_348-351m_mcrA_64, FR871732 AN07BC1_15_33, Kazan mud volcano sediment, AY883172 91 Methanocella paludicola SANAE, AB300467 LCM1443-12, carbonate rock, Lost City hydrothermal field, AY760635 Y42, soil, DQ663144 GJVT7LS03C1IIO 9|20|572M-798M-330M 97 GJVT7LS03C4OTT 5|693|572M-798M-330M 72 GJVT7LS03DGMFQ 1|7609|572M-798M-330M 57 MOBOcr43012, marine subsurface sediment, Marennes-Oleron Bay, AM942080 51 NANK-ME73118, Nankai Throught sediment, AY436547 Methanosarcina barkeri, Y00158 NANK-ME7326, Nankai Throught sediment, AY436542 89 54 Methanosarcina lacustris M5, AY260439 MOBOcr43024, marine subsurface sediment, Marennes-Oleron Bay, AM942086 98 Methanosarcina thermophila, AB353225 MOBOcr43994, marine subsurface sediment, Marennes-Oleron Bay, AM942101 Methanohalophilus mahii, AB353223 Methanosalsum zhilinae, AB353224 53 64 Methanococcoides alaskense, AB353221 Methanomethylovorans hollandica, AY260442 Methanosarcinales HMMVBeg-ME82, sediment, Haakon Mosby Mud Volcano, Barents Sea, AM407729 LCM1404-22, carbonate rock, Lost City hydrothermal field, AY760633 91 GJVT7LS03C05X4 6|63|330M 97 GJVT7LS03C8MF9 7|43|330M 62 62 GIB3I4J01EGHZT 4|468|347M 61 OL-KR43_68-73m_mcrA_11, Olkiluoto groundwater, Finland, FR871721 OL-KR40_348-351m_mcrA_17, Olkiluoto groundwater, Finland, FR871730 97 3667mcr07, Logatchev hydrothermal vent, Atlantic Ocean, EU495443 58 A2, freshwater sediment, EU495304 99 96 A14, freshwater sediment, EU495303 OL-KR42_156-160m_mcrA_44, Olkiluoto groundwater, Finland, FR871726 100 uncultured archaeon mcrA, Nankai Through, AB233460 mcrA42, hydrothermal vent chimney, Juan de Fuca Ridge, FJ640799 84 OL-KR40_348-351m_mcrA_30, Olkiluoto groundwater, Finland, FR871735 74 OL-KR40_348-351m_mcrA_33, Olkiluoto groundwater, Finland, FR871727 53 DR9IPCMCRCT3, dolomite aquifer, 896 meters, AY604059 99.6 ATB-EN-17137-M001d, biogas plant, FJ226612 Methanothermobacter wolfeii, AB300780 Methanobacteriales 89 Methanobacterium aarhusense, AY386125 54 Methanobacterium bryantii, AF313806 Methanobacterium subterramaeum, Asp̈ ö deep groundwater, Sweden Unfaunated-mcrA-05, rumen, AB244701 100 ATB-EN-5595-M020, biogas plant, FJ226631 67 99 ATB-EN5595, biogas plant, EU636864 95 Methanobrevibacter arboriphilus, AB300777 ME30-A5, subsurface sediment, AJ867760 83 GJVT7LS01A0JZU 8|57|572M 98 GJVT7LS01BA2X1 2|4606|572M eTm13, wetland soil, GU322089 60 D8A_MCRA1, 3.75 - 5 km deep terrestrial fracture system, AY768819 75 Methanothermococcus thermolithotrophicus, AB353226 90 ME-A, Rainbow Vent Field, Mid-Atlantic, AY354020 Methanothermococcus okinawensis, AB353229 Methanococcales 71 Methanotorris formiciicus, AB353227 99 88 Methanococcus voltae, X07793 Methanococcus vannielii MVOMCR, M16893 Methanotorris igneous, AB353228 Methanopyrus kandleri MKU57340, U57340 Methanopyrales 0.1

Figure 8: The phylogenetic distribution of the amino acid sequences of the OTUsof mcrA transcripts obtained detected in this study presented as a maximum likelihood tree. The sequences detected in this study are shown in red. Bootstrap support for nodes was calculated with 1000 random repeats and nodes with more than 50% support are indicated. The sequence codes are as described in Figure 6. BioMed Research International 15

󸀠 Table 4: The number of sequence reads, the observed and estimated number of OTUs, diversity coverage, and diversity index𝐻 ( )obtained by the HTP sequencing of bacterial and archaeal 16S rRNA and dsrBandmcrA transcripts. The diversity and OTU richness estimates were calculated based on equal number of sequence reads.

296m 328m 347m 415m 559m 572m 798m Number of reads 1220 893 9209 18425 17158 5377 996 Observed OTUs 45 46 35 63 83 169 49 Estimated richness Bacteria 16S Chao 161 294 73 126 161 367 104 Ace 412 355 111 219 355 587 139 Coverage % chao 28 16 48 50 56 46 47 ∗ 󸀠 𝐻 1.67 1.25 0.15 0.44 1.79 0.17 1.43 Number of reads 6322 12785 1377 2122 1223 1655 3277 Observed OTUs 139 67 32 45 26 26 6 Estimated richness Archaea 16S Chao 249 137 47 46 46 28 7 Ace 382 210 81 60 75 30 16 Coverage % chao 56 49 68 98 57 93 86 ∗ 󸀠 𝐻 1.06 0.81 1.91 1.23 0.80 1.04 0.83 Number of reads 8131 4144 12649 8628 2360 2249 — Observed OTUs 33 41 47 50 13 26 Estimated richness dsrB Chao 38 42 51 60 16 31 Ace 39 45 52 63 38 49 Coverage % chao 86.8 97.6 92.2 83.3 81.3 83.9 ∗ 󸀠 𝐻 2.29 2.65 0.69 1.03 1.93 1.81 Number of reads — 4188 4184 — — 6676 2324 Observed OTUs 4 2 2 1 Estimated richness mcrA Chao 4 2 2 1 Ace 5 0 0 0 Coverage % chao 100 100 100 100 ∗ 󸀠 𝐻 0.45 0.42 0.76 0.43 ∗ Normalized according to sample with the lowest number of reads.

References biosphere,” Open Journal of Ecology,vol.4,pp.468–487,2014. [7] L. Hallbeck and K. Pedersen, “Culture-dependent comparison [1] H. Castaneda and X. D. Benetton, “SRB-biofilm influence in of microbial diversity in deep granitic groundwater from two active corrosion sites formed at the steel-electrolyte interface sites considered for a Swedish final repository of spent nuclear when exposed to artificial seawater conditions,” Corrosion fuel,” FEMS Microbiology Ecology,vol.81,no.1,pp.66–77,2012. Science,vol.50,no.4,pp.1169–1183,2008. [2] Posiva Oy, “Olkiluoto site description 2011,” Report POSIVA [8] M. Itavaara,¨ M. Nyyssonen,A.Kapanen,A.Nousiainen,L.¨ 2011-02, Posiva Oy, 2012. Ahonen, and I. Kukkonen, “Characterization of bacterial diver- sitytoadepthof1500mintheOutokumpudeepborehole, [3] M. Nyyssonen,M.Bomberg,A.Kapanen,A.Nousiainen,P.¨ Fennoscandian Shield,” FEMS Microbiology Ecology,vol.77,no. Pitkanen,¨ and M. Itavaara,¨ “Methanogenic and sulphate-reduc- 2,pp.295–309,2011. ing microbial communities in deep groundwater of crystalline rock fractures in Olkiluoto, Finland,” Geomicrobiology Journal, [9] R. J. Parkes, B. A. Cragg, N. Banning et al., “Biogeochemistry vol.29,no.10,pp.863–878,2012. and biodiversity of methane cycling in subsurface marine sedi- [4] S. A. Haveman, K. Pedersen, and P. Ruotsalainen, “Distribution ments (Skagerrak, Denmark),” Environmental Microbiology,vol. and metabolic diversity of microorganisms in deep igneous rock 9, no. 5, pp. 1146–1161, 2007. aquifers of Finland,” Geomicrobiology Journal,vol.16,no.4,pp. [10] G. Webster, H. Sass, B. A. Cragg et al., “Enrichment and cultiva- 277–294, 1999. tion of prokaryotes associated with the sulphate-methane tran- [5]S.A.HavemanandK.Pedersen,“Distributionofculturable sition zone of diffusion-controlled sediments of Aarhus Bay, microorganisms in Fennoscandian shield groundwater,” FEMS Denmark, under heterotrophic conditions,” FEMS Microbiology Microbiology Ecology,vol.39,no.2,pp.129–137,2002. Ecology,vol.77,no.2,pp.248–263,2011. [6]M.Bomberg,M.Nyyssonen,A.Nousiainenetal.,“Evaluation¨ [11] J. Leloup, A. Loy, N. J. Knab, C. Borowski, M. Wagner, and of molecular techniques in characterization of deep terrestrial B. B. Jørgensen, “Diversity and abundance of sulfate-reducing 16 BioMed Research International

microorganisms in the sulfate and methane zones of a marine [27] N. Bano, S. Ruffin, B. Ransom, and J. T. Hollibaugh, “Phy- sediment, Black Sea,” Environmental Microbiology,vol.9,no.1, logenetic composition of Arctic ocean archaeal assemblages pp. 131–142, 2007. andcomparisonwithAntarcticassemblages,”Applied and [12] L. Holmkvist, T. G. Ferdelman, and B. B. Jørgensen, “A cryptic Environmental Microbiology,vol.70,no.2,pp.781–789,2004. sulfur cycle driven by iron in the methane zone of marine sed- [28] S. M. Barns, R. E. Fundyga, M. W. Jeffries, and N. R. Pace, iment (Aarhus Bay, Denmark),” Geochimica et Cosmochimica “Remarkable archaeal diversity detected in a Yellowstone Na- Acta,vol.75,no.12,pp.3581–3599,2011. tional Park hot spring environment,” Proceedings of the National [13] N. Iversen and B. B. Jorgensen, “Anaerobic methane oxida- Academy of Sciences of the United States of America,vol.91,no. tion rates at the sulfate-methane transition in marine sedi- 5, pp. 1609–1613, 1994. ments from Kattegat and Skagerrak (Denmark),” Limnology & [29] J. Geets, B. Borremans, L. Diels et al., “DsrB gene-based Oceanography,vol.30,no.5,pp.944–955,1985. DGGE for community and diversity surveys of sulfate-reducing [14] Y.Koizumi, S. Takii, M. Nishino, and T. Nakajima, “Vertical dis- bacteria,” Journal of Microbiological Methods,vol.66,no.2,pp. tributions of sulfate-reducing bacteria and methane-producing 194–205, 2006. archaea quantified by oligonucleotide probe hybridization in [30] M.Wagner,A.J.Roger,J.L.Flax,G.A.Brusseau,andD.A.Stahl, the profundal sediment of a mesotrophic lake,” FEMS Micro- “Phylogeny of dissimilatory sulfite reductases supports an early biology Ecology,vol.44,no.1,pp.101–108,2003. origin of sulfate respiration,” Journal of Bacteriology,vol.180,no. [15]P.Aalto,J.Helin,S.Lindgrenetal.,Baseline Report for Infiltra- 11, pp. 2975–2982, 1998. tion Experiment, WR 2011–25, Posiva Oy, Olkiluoto, Finland, [31] B. A. Hales, C. Edwards, D. A. Ritchie, G. Hall, R. W. Pickup, 2011. and J. R. Saunders, “Isolation and identification of methanogen- [16]K.Pedersen,A.F.Bengtsson,J.S.Edlund,andL.C.Eriksson, specific DNA from blanket bog peat by PCR amplification and “Sulphate-controlled diversity of subterranean microbial com- sequence analysis,” Applied and Environmental Microbiology, munities over depth in deep groundwater with opposing gradi- vol.62,no.2,pp.668–675,1996. ents of sulphate and methane,” Geomicrobiology Journal,vol.31, [32] P. D. Schloss, S. L. Westcott, T. Ryabin et al., “Introducing no.7,pp.617–631,2014. mothur: open-source, platform-independent, community-sup- [17] K. Pedersen, J. Arlinger, S. Erikson et al., Microbiology of ported software for describing and comparing microbial com- Olkiluoto Groundwater, Results and Interpretations 2007,WR munities,” Applied and Environmental Microbiology,vol.75,no. 2008-34, 2008. 23, pp. 7537–7541, 2009. [18] Posiva, “Olkiluoto site description 2008, part 1,” POSIVA 2009- [33] E. Pruesse, C. Quast, K. Knittel et al., “SILVA: a comprehensive 01, Posiva Oy, 2009. online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB,” Nucleic Acids Research, [19] A. Karki¨ and S. Paulamaki,¨ “Petrology of Olkiluoto,” POSIVA vol. 35, no. 21, pp. 7188–7196, 2007. 2006-02, Posiva Oy, 2006. [34] V. Zverlov, M. Klein, S. Lucker¨ et al., “Lateral gene transfer of [20] H. Ahokas, E. Tammisto, and T. Lehtimaki,¨ “Baseline head in dissimilatory (bi)sulfite reductase revisited,” Journal of Bacteri- Olkiluoto,” WR 2008-69, Posiva Oy, Eurajoki, Finland, 2008. ology, vol. 187, no. 6, pp. 2203–2208, 2005. [21] R. L. Kepner and J. R. Pratt, “Use of fluorochromes for direct [35] T. Z. DeSantis, P. Hugenholtz, N. Larsen et al., “Greengenes, enumeration of total bacteria in environmental samples: past a chimera-checked 16S rRNA gene database and workbench and present,” Microbiological Reviews,vol.58,no.4,pp.603– compatible with ARB,” AppliedandEnvironmentalMicrobiol- 615, 1994. ogy,vol.72,no.7,pp.5069–5072,2006. [22] M. Itavaara,¨ M.-L. Vehkomaki,¨ and A. Nousiainen, “Sulphate- [36] R. C. Edgar, “MUSCLE: multiple sequence alignment with high reducing bacteria in ground water samples from Olkiluoto— accuracy and high throughput,” Nucleic Acids Research,vol.32, analyzed by quantitative PCR,” Tech. Rep. WR 2008-82, 2008. no.5,pp.1792–1797,2004. [23] U. Edwars, T. Rogall, H. Blocker, M. Emde, and E. C. Bottger, [37] S. Guindon and O. Gascuel, “A simple, fast, and accurate algo- “Isolation and direct complete nucleotide determination of rithm to estimate large phylogenies by maximum likelihood,” entire genes. Characterization of a gene coding for 16S riboso- Systematic Biology,vol.52,no.5,pp.696–704,2003. mal RNA,” Nucleic Acids Research,vol.17,no.19,pp.7843–7853, 1989. [38] T. H. Jukes and C. R. Cantor, “Evolution of protein molecules,” in Mammalian Protein Metabolism,H.N.Munro,Ed.,pp.21– [24] G. Muyzer, E. C. de Waal, and A. G. Uitterlinden, “Profiling 132, Academic Press, New York, NY, USA, 1969. of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified [39] S. Whelan and N. Goldman, “A general empirical model of genes coding for 16S rRNA,” Applied and Environmental Micro- protein evolution derived from multiple protein families using a biology,vol.59,no.3,pp.695–700,1993. maximum-likelihood approach,” Molecular Biology and Evolu- tion,vol.18,no.5,pp.691–699,2001. [25] R. Großkopf, P. H. Janssen, and W. Liesack, “Diversity and structure of the methanogenic community in anoxic rice paddy [40] Ø.Hammer,D.A.T.Harper,andP.D.Ryan,“Past:paleontolog- soil microcosms as examined by cultivation and direct 16S ical statistics software package for education and data analysis,” rRNA gene sequence retrieval,” Applied and Environmental Palaeontologia Electronica, vol. 4, no. 1, p. 9, 2001. Microbiology, vol. 64, no. 3, pp. 960–969, 1998. [41] S. S. Shapiro and M. B. Wilk, “An analysis of variance test for [26] D. A. Stahl and R. Amann, “Development and application of normality (complete samples),” Biometrika,vol.52,pp.591–611, nucleic acid probes in bacterial systematics,” in Nucleic Acid 1965. Techniques in Bacterial Systematics, E. Stackebrandt and M. [42] M. A. Stephens, “Tests based on EDF statistics,”in Goodness-of- Goodfellow, Eds., pp. 205–248, John Wiley and Sons, New York, Fit Techniques, R. B. D'Agostino and M. A. Stephens, Eds., pp. NY, USA, 1998. 97–194, Marcel Dekker, New York, NY, USA, 1986. BioMed Research International 17

[43] S. D’Hondt, S. Rutherford, and A. J. Spivack, “Metabolic activity of subsurface life in deep-sea sediments,” Science,vol.295,no. 5562, pp. 2067–2070, 2002. [44]I.Roalkvam,S.L.Jørgensen,Y.Chenetal.,“Newinsightinto stratification of anaerobic methanotrophs in cold seep sediments,” FEMS Microbiology Ecology,vol.78,no.2,pp.233–243, 2011. [45] J. Grote, Physiology, ecology, and genomics of facultative chemo- autotrophic Epsilonproteobacteria in marine pelagic redoxclines [Ph.D. thesis], University of Rostock, Rostock, Germany, 2009. [46]K.Takai,M.Suzuki,S.Nakagawaetal.,“Sulfurimonas para- lvinellae sp. nov., a novel mesophilic, hydrogen- and sulfur- oxidizing chemolithoautotroph within the Epsilonproteo- bacteria isolated from a deep-sea hydrothermal vent polychaete nest, reclassification of Thiomicrospira denitrificans as Sulfuri- monas denitrificans comb. nov. and emended description of the genus Sulfurimonas,” International Journal of Systematic and Evolutionary Microbiology,vol.56,no.8,pp.1725–1733,2006. [47] S. Glaubitz, T. Lueders, W.-R. Abraham, G. Jost, K. Jurgens,¨ and 13 M. Labrenz, “ C-isotope analyses reveal that chemolithoau- totrophic Gamma- and Epsilon-proteobacteria feed a microbial food web in a pelagic redoxcline of the central Baltic Sea,” Environmental Microbiology,vol.11,no.2,pp.326–337,2009. [48] M. F. Haroon, S. Hu, Y. Shi et al., “Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage,” Nature,vol.500,no.7464,pp.567–570,2013. [49]V.J.Orphan,C.H.House,K.-U.Hinrichs,K.D.McKeegan, and E. F. DeLong, “Multiple archaeal groups mediate methane oxidation in anoxic cold seep sediments,” Proceedings of the National Academy of Sciences of the United States of America, vol.99,no.11,pp.7663–7668,2002. [50]S.Glaubitz,T.Lueders,W.R.Abraham,G.Jost,K.Jurgens,¨ and M. Labrenz, “13C-isotope analyses reveal that chemolithoau- totrophic Gamma- and Epsilonproteobacteria feed a microbial food web in a pelagic redoxcline of the central Baltic Sea,” Environmental Microbiology,vol.11,no.2,pp.326–337,2009. [51] K. Knittel and A. Boetius, “Anaerobic oxidation of methane: progress with an unknown process,” Annual Review of Micro- biology,vol.63,pp.311–334,2009. [52] C. Wrede, A. Dreier, S. Kokoschka, and M. Hoppert, “Archaea in symbioses,” Archaea,vol.2012,ArticleID596846,11pages, 2012. [53] J. Milucka, T. G. Ferdelman, L. Polerecky et al., “Zero-valent sulphur is a key intermediate in marine methane oxidation,” Nature,vol.491,no.7425,pp.541–546,2012. [54] K. Pedersen, “Metabolic activity of subterranean microbial communities in deep granitic groundwater supplemented with methane and H2,” The ISME Journal,vol.7,no.4,pp.839–849, 2013. [55]D.R.Lovley,E.E.Roden,E.J.P.Phillips,andJ.C.Woodward, “Enzymatic iron and uranium reduction by sulfate-reducing bacteria,” Marine Geology,vol.113,no.1-2,pp.41–53,1993. [56] E. Dalla Vecchia, E. I. Suvorova, J. Maillard, and R. Bernier- Latmani, “Fe(III) reduction during pyruvate fermentation by Desulfotomaculum reducens strain MI-1,” Geobiology,vol.12,no. 1, pp. 48–61, 2014. International Journal of Peptides

Advances in BioMed Stem Cells International Journal of Research International International Genomics Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 Virolog y http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014

Journal of Nucleic Acids

Zoology International Journal of Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014

Submit your manuscripts at http://www.hindawi.com

Journal of The Scientific Signal Transduction World Journal Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014

Genetics Anatomy International Journal of Biochemistry Advances in Research International Research International Microbiology Research International Bioinformatics Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014

Enzyme International Journal of Molecular Biology Journal of Archaea Research Evolutionary Biology International Marine Biology Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014